YOLO-based robotic grasping

被引:2
|
作者
Kim, Munhyeong [1 ]
Kim, Sungho [1 ]
机构
[1] Yeungnam Univ, Dept Elect Engn, Gyongsan, South Korea
来源
2021 21ST INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2021) | 2021年
关键词
Deep learning; object detection; robotic grasping; bin picking;
D O I
10.23919/ICCAS52745.2021.9649837
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Waste is causing a lot of problems around the world and there is a problem of poor recycling. To separate garbage collection, various wastes shall be detected and recognized, which shall be carried out in real time. To address these issues, this paper proposes YOLO-based robotic grasping methods. The limitations of existing deep learning-based robotic grasping methods predict grasping points in all images and do not recognize objects. Considering this, we perform object detection and capture point derivation by processing images with the proposed area restriction method after detection and recognition based on YOLO, an one-stage object detection.
引用
收藏
页码:1120 / 1122
页数:3
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